---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-football
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-finetuned-ner-football

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1445
- Precision: 0.8577
- Recall: 0.9018
- F1: 0.8792
- Accuracy: 0.9625

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 199  | 0.2021          | 0.7253    | 0.8035 | 0.7624 | 0.9363   |
| No log        | 2.0   | 398  | 0.1521          | 0.8362    | 0.8944 | 0.8643 | 0.9589   |
| 0.2566        | 3.0   | 597  | 0.1445          | 0.8577    | 0.9018 | 0.8792 | 0.9625   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1